Intensix’s software tries to anticipate changes in a patient’s condition before they happen. Similar technology by other companies has been employed for home healthcare and for admitted patients, but this would be a big deal, to try to buy a couple extra hours, perhaps minutes, that could save the life of someone in intensive care.

“Predictive modeling coupled with machine learning represents a paradigm shift in the delivery of high-acuity healthcare,” says Intensix CEO Gal Solomon. “This support will enable the company to expand and advance the capabilities of our platform and accelerate deployment in the US and EU.”

“The explosion of patient data, via electronic health records, sensors, and medical devices, provides physicians with an untapped wealth of new information,” added Pitango’s Ittai Harel. “Machine learning and predictive analytics have the power to harness this data, offering great value to the healthcare industry, particularly in the area of critical care.”

This isn’t Pitango’s first foray into the early-detection part of the health sector. They led the November 2012 Series E funding round in patient supervision startup #EarlySense, investing again last year in their $25 million Series G in June.

Predictive or preventive care has been a trend for several years. The health benefits from these types of systems are obvious, but the financial and logistical payoffs are large as well. With a variety of home-monitoring products hitting the market and better ways to keep track of patients’ compliance with their own rehab programs or prescriptions, doctors can get their patients back on track before they have to be readmitted to a hospital.

That saves hospitals valuable room in their wards and frees up doctors’ time to focus on less predictable medical crises.

Examples are prolific. The Carolinas HealthCare System (CHS) cut readmission rates by a third using software from California startup Predixion. Tel Aviv’s private hospital Assuta also uses home health-monitoring system to red-flag problems as they develop.

“With a focus on adhering to treatment,” Jeff Elton and Arda Ural, specialists in predictive health intelligence at Accenture Strategy, wrote way back in 2014, “patients, providers, risk bearers, and life science companies would all be beneficiaries.”